Integrating artificial intelligence into haematology training and practice: Opportunities, threats and proposed solutions

Abstract

There remains a limited emphasis on the use beyond the research domain of artificial intelligence (AI) in haematology and it does not feature significantly in postgraduate medical education and training. This perspective article considers recent developments in the field of AI research in haematology and anticipates the potential benefits and risks associated with its deeper integration into the specialty. Anxiety towards the greater use of AI in healthcare stems from legitimate concerns surrounding data protection, lack of transparency in clinical decision-making, and erosion of the doctor-patient relationship. The specialty of haematology has successfully embraced multiple disruptive innovations. We are at the cusp of a new era of closer integration of AI into routine haematology practice that will ultimately benefit patient care but to harness its benefits the next generation of haematologists will need access to bespoke learning opportunities with input from data scientists.

Artificial intelligence: Training the trainer

“…A basic understanding and knowledge of the limitations and dangers are just a few aspects medical use of AI requires. In this context the article by Chai et al 1 is an enrichment.…”

“…The situation is similar with AI in haematology: The first applications were designed and tested in the 1990s 4,5 but now is the time when the required calculation power becomes affordable and hence AI applications widely available. 6 When it comes to the integration of AI in haematological practice, Chai et al 1 provide a number of nice and relevant examples. Since it is a rather loose collection of methods and applications, I would like to emphasise the ground-breaking aspects.…”

“…The technological implementation remains a challenge but is not the limiting factor, which is the willingness to incorporate AI in haematological judgements. Like most novel technologies, AI also frightens both physicians and patients as outlined by Chai et al 1 However, the potential, the opportunities and benefits are so enormous, they require and deserve educational efforts on all levels. Let us train the trainer!…”

“…Although I have to admit that ANN are increasingly designed as self‐learning networks, they still require human validation, which just shifts the task a little bit. To address the established haematologists that are in leading positions, I hope the current discussion in the British Journal of Haematology 1–3 will contribute.…”

Predicting the natural history of artificial intelligence in travel medicine

“…Concerns about erosion of the clinician–patient relationship, loss of essential clinical skills, data privacy and the risks associated with biased data should be openly discussed. 10 Travel medicine, as one of the newest areas of clinical practice and research with a truly global dimension, is uniquely positioned to harness the exciting benefits of AI.…”